The cloud is hype.

It is the hype around a logical step in the progression of IT and somehow the term ‘The Cloud’ has stuck in the minds of vendors, the media and, to a lesser extent, the customer.

Unlike most terms that we IT is used to, ‘The Cloud’ is not specific – a customer is never going to want to ‘buy a cloud’ and nobody can, with any authority, say what the cloud is. Disagreement exists on the definition of the cloud and cloud computing – academics, vendors, analysts and customers all disagree to varying degrees. This creates confusion as well as opportunities – where every blogger, journalist, vendor, developer and website can slap a cloud sticker on their product, service, website, marketing material and even the forehead of their marketing VP, and deem it to be ‘The Cloud’ or ‘<some new form> Cloud’.

In a world of no definitions, any definition is valid.

So while I am loathe to add yet another definition to the world of cloud computing, it seems that any conversation about cloud computing starts with some common understanding about what the base concepts and principles are.  I tackled the question which asks “If cloud computing is based on existing technologies, why has it suddenly become important and talked about only recently?”.

I believe that the answer is that the base technologies have matured, leading to new computing models, which business is able to realise the value and finally it leads to new computing models based, if you trace it back, to the technologies which we talk about as being part of cloud computing. 

I have written an essay on this an broken it down into four parts, reflecting the layers and progression, and I will post this over the next few days.

Part 1 : Base Technology


At its most basic, cloud computing is about rapidly providing and disposing of computer resources quickly, easily and on demand.

Think about Mozy backup – you can get backup for your PC in a few minutes without having to go out and buy a backup disk, plug it in, power it up, install drivers, format, etc. Instead, you download a piece of software, put in your credit card details and ta-da, you have a good backup solution until you don’t want it anymore, in which case you simply cancel the service and you don’t have an external disk lying around that needs to be disposed of. The Mozy example demonstrates computing resources (backup) provisioned rapidly (no waiting for hardware and no hardware setup) that is almost immediately available and can be disposed of just as fast. It is, by a broader definition, Cloudy.

Unfortunately, instantly providing computing resources is not easy as one would think (as anyone who has seen data centre lead times is aware), so the seemingly simple objective of providing computing resources utilises some base technologies that are generally considered part of cloud computing.

It is the base technologies that have gradually matured over time that have given us the ability to achieve the goal of utilizing computing resources easily, and the following four are the primary influencing technologies.


Obviously, if you want resources and want them now, it doesn’t make sense to have to physically get a new machine, install it in a rack, plug it in and power it up. So a virtual machine that can be spun up within a couple of minutes is key to the ability to provide for the demand. Virtualization also forces the removal of specialized equipment on which software may depend by providing a baseline, non-specialized, machine abstraction.

Shared Resources

Individual resource consumers do not want to buy their resources up front – it would go against the idea of ‘on demand’. So it makes sense that it would be better to create a pool of resources that are potentially available to everyone and are allocated and de-allocated to individual consumers’ needs.  Multi-tenancy is a further concept behind the sharing of resources, where multiple customers can share a single physical resource at the same time.  Virtual machines running on the same physical hardware is an example of multi-tenancy.


In order to make all of these shared, virtualized resources available on demand, some automation tools need to sit between the request for a resource and the fulfilment of the request – it has to be zero touch by an expensive engineer. Sending an email and waiting for someone in operations to get around to it is not exactly rapid provisioning. So a big part of cloud computing are the tools and infrastructure to spin up machines, bring new hardware online, handle failures, patch software, de-allocate and decommission machines and resources etc.

Abstracted Services

Computing resources need not be limited to specific low level hardware resources such as an addressable memory block or a spindle on a disk – not only is it generally unnecessary, but technically impossible if coupled with quick, on demand resources. A fundamental technology advancement of the cloud is the increased use and availability of abstracted computing resources (consumed as services). While virtual machine is an abstraction of a much more complicated physical layer, the abstractions become much higher-level where resources are exposed as services, so a consumer doesn’t ask for a specific disk, but rather requests resources from a storage service where all of the complicated stuff is abstracted away and taken care of.

These technical solutions to the demand problem have, in turn, had some interesting side effects on existing models of computing. The public cloud, utility pricing, commodity nodes and service specializations have emerged as rediscovered computing models that are driving the adoption of cloud technologies.

Continue to part 2 : ‘Computing Models’

Simon Munro